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Any other operation on untyped constants results in an untyped constant of the same kind; that is, a boolean, integer, floating-point, complex, or string constant. If the untyped operands of a binary operation (other than a shift) are of different kinds, the result is of the operand's kind that appears later in this list: integer, rune, floating-point, complex. For example, an untyped integer constant divided by an untyped complex constant yields an untyped complex constant.

Constant expressions are always evaluated exactly; intermediate values and the constants themselves may require precision significantly larger than supported by any predeclared type in the language. The following are legal declarations:

The divisor of a constant division or remainder operation must not be zero:

the function calls and communication happen in the order
f()
,
h()
,
i()
,
j()
,
<-c
,
g()
, and
k()
. However, the order of those events compared to the evaluation and indexing of
x
and the evaluation of
y
is not specified.

At package level, initialization dependencies override the left-to-right rule for individual initialization expressions, but not for operands within each expression:

Floating-point operations within a single expression are evaluated according to the associativity of the operators. Explicit parentheses affect the evaluation by overriding the default associativity. In the expression
x + (y + z)
the addition
y + z
is performed before adding
x
.

Notice that any Uniform distribution has uncountable number of modes having equal density value; therefore it is considered as a homogeneous population.

The discrete uniform distribution describes the distribution of n equally likely events (labeled with the integers from 1 to n), each with probability 1/n.

If X is a discrete uniform random variable with parameter n, then the mean, and variance are as follows:

E(X) = (n+1)/2, Var(X) = (n -1) /12

For two populations use the F-test. For 3 or more populations, there is a practical rule known as the"Rule of 2". In this rule, one divides the highest variance of a sample by the lowest variance of the other sample. Given that the sample sizes are almost the same, and the value of this division is less than 2, then the variations of the populations are almost the same.

Notice:
This important condition in analysis of variance (ANOVA and the t-test for mean differences) is commonly tested by the Levene test or its modified test known as the Brown-Forsythe test. Interestingly, both tests rely on the homogeneity of variances condition!